import numpy as np
import pandas as pd
import plotly.express as px

import qplot.activate

from qplot import get_axes, set_mpl_layout, set_plotly_layout, set_pd_backend

2020-07-31 08:16:38.201 | INFO     | qplot.activate:<module>:26 - IPython detected, applying inline plotting and svg figure format.

# generate data

dates = pd.date_range('2010-01-01', '2020-01-01')
df = pd.DataFrame(np.random.randn(len(dates), 5), index=dates, columns=list('ABCDE')).cumsum()
df.head()

	A	B	C	D	E
2010-01-01	0.121563	0.672453	0.321454	-0.679192	0.111542
2010-01-02	1.232560	0.456268	-1.511775	0.148773	-0.615827
2010-01-03	2.288173	0.559926	-2.345664	1.566988	0.218227
2010-01-04	1.371283	1.695923	-0.581207	2.754848	-3.091487
2010-01-05	-0.284057	2.679610	0.110264	2.237199	-1.071573

Matplotlib static plots

ax = get_axes()
df.plot(ax=ax)
set_mpl_layout(ax, title='Time series', xlabel='dates', ylabel='values')

fig, (ax1, ax2) = get_axes(height=6, ncols=2, wratios=[3, 2], return_fig=True)
df['A'].plot(ax=ax1)
df['B'].plot(ax=ax2)
set_mpl_layout(ax1, legend_outside=False, ylabel='values')
set_mpl_layout(ax2)
fig.autofmt_xdate()  # to avoid xticklabels overlap 

Plotly interactive plots

fig = px.line(df, x=df.index, y='A')
set_plotly_layout(fig, title='A plot', xlabel='dates', ylabel='values', small=True)
fig.show()

# create long df (unstack columns)
df.index.name = 'date'
df.columns.name = 'column'
df_long = df.unstack().to_frame(name='value').reset_index()
df_long

	column	date	value
0	A	2010-01-01	0.121563
1	A	2010-01-02	1.232560
2	A	2010-01-03	2.288173
3	A	2010-01-04	1.371283
4	A	2010-01-05	-0.284057
...	...	...	...
18260	E	2019-12-28	-132.781910
18261	E	2019-12-29	-132.808952
18262	E	2019-12-30	-133.019605
18263	E	2019-12-31	-133.827087
18264	E	2020-01-01	-135.437963

18265 rows × 3 columns

fig = px.line(df_long, x='date', y='value', color='column')
set_plotly_layout(fig, title='scatter plot', height=10)
fig.show()

df.loc[:, 'S'] = df['C'].abs()
df.loc[:, 'WD'] = list(df.index.weekday)
fig = px.scatter(df.iloc[:50], x='A', y='B', size='S', animation_frame='WD', category_orders={'WD': range(7)})
set_plotly_layout(fig, xlabel='A values', ylabel='B values', height=10)
fig.show(rederer='notebook')